1.1k citations · 1.1k across the 7 of their papers we have counts for
3 papers · 1 filter
Learning to Generate Image Embeddings with User-level Differential Privacy
Zheng Xu, Maxwell Collins, Yuxiao Wang +6
Small on-device models have been successfully trained with user-level differential privacy (DP) for next word prediction and image classification tasks in the past. However, existi…
Mixed Federated Learning: Joint Decentralized and Centralized Learning
Sean Augenstein, Andrew Hard, Lin Ning +4
Federated learning (FL) enables learning from decentralized privacy-sensitive data, with computations on raw data confined to take place at edge clients. This paper introduces mixe…
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training
Andrew Hard, Kurt Partridge, Neng Chen +9
We trained a keyword spotting model using federated learning on real user devices and observed significant improvements when the model was deployed for inference on phones. To comp…